Result of benchmark functions. by Mingjun Li (178925)

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Reward function related parameters. by Honglei Pang (22693724)

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Comparison of algorithm search curves. by Bowen Li (200859)

“…Then, combining with the idea of fast density clustering algorithm, the number of hidden layer neurons of RBF is determined by finding the point with the highest density and using it as the hidden layer neuron. …”

Results of 7 benchmarking functions in 50 dimensions. by M. A. JiMing (19207527)

Results of 7 benchmarking functions in 30 dimensions. by M. A. JiMing (19207527)

Functional enrichment of gene clusters identified in up-regulated drought tolerant network (uDTN) using MCL algorithm. by Sanchari Sircar (198485)

Run times of two algorithms. by Gourab Saha (8987405)

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Distribution of FEV1/FVC in pulmonary function tests with discrepant interpretations between the algorithm and the clinicians. by Yuh-Chin T. Huang (17867207)

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Summary of classical and CEC-based benchmark test functions used in this study. by Mahmood A. Jumaah (22272371)

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Pseudo-code of DMDDPG algorithm. by Guohua Cao (697580)

“…Next, a reward function is designed by integrating the decoupled multi-agent deterministic deep deterministic policy gradient (DMDDPG) algorithm. …”

The pseudocode for the NAFPSO algorithm. by Huichao Guo (14515171)

“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”

PSO algorithm flowchart. by Huichao Guo (14515171)

“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”

Network utility for different desirability functions. by Maryam Chinipardaz (18098413)

CEC2017 basic functions. by Tengfei Ma (597633)

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Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

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Automatic translation error detection based on fuzzy decision tree algorithm. by Danqiangyu Zhou (22146196)

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Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm by Gelio Alves (51850)

“…A major challenge in mass-spectrometry-based metaproteomics is accurately identifying and quantifying biological functions across the full taxonomic lineage of microorganisms. …”

Load curves of residential and IT sector loads with CS algorithm based DSM. by Manoj Kumar V. (18196645)

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Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”